원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.9
2016.09
pp.149-156
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Sentiment analysis is shown significant and indispensable status in hot topic, public-opinion poll, knowledge acquiring and recommended goods fields, which is the fundamental work for natural language processing. This paper proposes an approach to build the Tibetan sentiment dictionary and to calculate the sentiment value base on the Tibetan semantic relations. We test our approach on experimental corpus crawled from Sina weibo and the experimental results demonstrate good performance on Tibetan language.
목차
Abstract
1. Introduction
2. Related Work
2.1. The Supervised Learning Method
2.2. The Unsupervised Learning Method
3. Tibetan Sentiment Calculation
3.1. The Tibetan Sentiment Dictionary
3.2. The Sentiment Calculation Model
4. Experimental Results and Analysis
4.1. Experimental Data
4.2. The Experimental Procedure
5. Conclusions
Acknowledgement
References
1. Introduction
2. Related Work
2.1. The Supervised Learning Method
2.2. The Unsupervised Learning Method
3. Tibetan Sentiment Calculation
3.1. The Tibetan Sentiment Dictionary
3.2. The Sentiment Calculation Model
4. Experimental Results and Analysis
4.1. Experimental Data
4.2. The Experimental Procedure
5. Conclusions
Acknowledgement
References
저자정보
참고문헌
자료제공 : 네이버학술정보